Cecilia Van Cauwenberghe from Frost & Sullivan’s TechVision Group, provides a cancer focus, in particular, she details breakthrough technologies that allow leveraging biomarkers for oncology
According to Frost & Sullivan, biomarker analytics has become one of the most in-demand branches of science relevant to the process of drug discovery and development in the pharmaceutical industry (Iyer, 2019). Looking to accelerating the drug development process, several advances have been made in the area of biomarker analytics during the past five years. One of the most remarkable technologies propelling a substantial increase in the efficiency of biomarker analytics is the use of artificial intelligence (AI).
AI-based biomarker screening in oncology allows leveraging the huge data deluges generated through various omics platforms by using machine learning and deep learning techniques. This innovative trend is resulting in highly effective in scrutinising through data and identifying critical cancer biomarkers through pattern recognition.
Predictive and prognostic biomarkers
Both predictive and prognostic biomarkers represent a central element in targeted oncology drug discovery and development (Van Cauwenberghe and Iyer, 2017). Cancer biomarkers are paving the way for personalised medicine and precision oncology. According to the authors, cancer biomarkers provide critical information about the mechanism of action of a drug or target, which derives a deeper understanding of the carcinogenesis process, hence allowing matching patient characteristics specifically to the most appropriate treatment.
Predictive biomarkers are used to provide the best treatment indication with a greater probability of response to a certain specific chemotherapeutic agent, also considering treatment-related side effects. Prognostic biomarkers, on the other hand, are used to identify patients with different clinical outcomes associated with somatic mutations, alterations in DNA methylation, germline polymorphisms, serum cytokine
levels, expression of micro-RNA (miRNA) as well as circulating tumour cells (CTCs) in blood. The paramount goal relies on the precise identification of highly specific and sensitive biomarkers consistent with clinical outcomes or antitumour effects.
Disrupting innovations in cancer biomarkers MicroRNAs The deep interaction between abnormalities in genes coding for proteins and noncoding microRNAs (miRNAs) was among the most exciting discoveries in oncology during the last decade (Berindan-Neagoe et al., 2014). Such interplay has reshaped cancer research. According to Berindan-Neagoe, miRNAs are considered practically as genomic trash.
Now, the scientists show consensus assuming miRNAs as a crucial matter for cancer initiation, progression and dissemination. Naturally occurring miRNAs consists of very short transcripts, which although generate neither protein nor amino acids, act as protein expression regulators during diverse cellular processes, including growth, development and differentiation at the transcriptional, posttranscriptional and/or translational level. Under this perspective, miRNAs have demonstrated to be deeply involved in all cancer hallmarks.
Therefore, miRNAs can be used as cancer biomarkers. In the opinion of Filipów and Łaczmański (2019), miRNAs are promising molecules for clinical biomarkers.
The use of genome-wide detection methods, empowered with AI-based diagnostic technologies, allows identifying ubiquitously aberrant expression profiles of miRNAs for a wide range of human cancers with high specificity and sensitivity (Lan et al., 2015). Due to miRNAs can be detected in tissue, blood and other body fluids with a high stability their facility of adoption as clinical biomarkers have been promptly recognised.
Proteomics, transcriptomics and metabolomics
There is a rising demand for the discovery and development of new proteomic biomarkers in oncology. Proteomic biomarkers are gaining increasing attention in companion diagnostic platforms. Therefore, both medical diagnostics and pharmaceutical companies are working closely to fuel groundbreaking innovations that will enable enhanced diagnosis and management of a wide range of cancer indications. Proteomic markers may enable the discovery and development of new drug targets, they are ideally poised to transform the future of cancer diagnosis and management (Patel et al., 2019). Transcriptomic biomarkers for cancer diagnosis and management are also garnering attention as cancer biomarkers.
Additionally, these developments are strengthened by adjacent technologies such as liquid biopsy, which is leading the industry transformation toward the use of non-invasive or minimally invasive techniques for cancer screening and treatment monitoring applications (Iyer, 2019).
Metabolomics research is rapidly evolving to include metabolic flux analysis in disease and healthy conditions to enable deeper insights across metabolomic signatures. Pharmaceutical companies are looking to leverage metabolomic data to facilitate novel drug target discoveries. Indeed, rapid technological advances have enabled the multiplexed analyses of a wide range of metabolites.
Metabolomic signature panels are likely to become more important for cancer profiling and monitoring applications in the near future (Van Cauwenberghe and Iyer, 2017). Indeed, metabolomic profiling companies are likely to extend the application of their technology platforms beyond research toward predictive, diagnostic and monitoring applications in cancer care. The convergence of metabolic advances with cloud-based and computational tools is likely to fuel growing research and clinical interest in this space.
Final remarks
The clinical relevance of novel cancer biomarkers that are being discovery will be the key factor for determining their successful applications in clinical
settings. Growing pharma and diagnostic collaborations are likely to transform cancer management toward the path of precision medicine and personalised medicine applications.
As more gene therapies find acceptance across the growing regulatory landscape, there will be a growing shift toward biopharma and targeted therapy approaches in cancer management, which will eventually lead to a decrease in treatment toxicities.
Acknowledgements
I would like to thank all contributors from the industry involved with the development and delivery of this article from Frost & Sullivan.
References
Berindan-Neagoe, I., Monroig, P .D.C., Pasculli, B. and Calin, G.A., 2014. MicroRNAome genome: a treasure for cancer diagnosis and therapy. CA: a cancer journal for clinicians, 64(5), pp.311-336.
Filipów, S. and Łaczmański, Ł., 2019. Blood circulating miRNAs as cancer biomarkers for diagnosis and surgical treatment response. Frontiers in genetics, 10.
Iyer, V. 2019. Innovations in Biomarker Analytics – Tracking the Market Landscape of Companies Striving to Derive Actionable Insights from the Data Deluge through the incorporation of Artificial Intelligence. TechVision Analysis. D8DA. Frost & Sullivan
Lan, H., Lu, H., Wang, X. and Jin, H., 2015. MicroRNAs as potential biomarkers in cancer: opportunities and challenges. BioMed research international, 2015.
Patel, A., Soneji, D., Parikh, P . and Kumar, M., 2019. Biomarkers in immuno-oncology: A review article.
Van Cauwenberghe, C., Iyer, V. 2017. Breakthroughs in Leveraging Biomarkers for Oncology. Accelerating Solutions for Cancer Diagnostics and Therapeutics. TechVision Analysis. D7B2. Frost & Sullivan.
